11 5 2020

Aim - hypothesis - inkl søjleplot og map plot Mette

Materiale - oversigt over dataset - Mette Christof

Metode 1 - clean flowchart - Mette Christof

Metode 2 - analyse flowchart - Mette Christof

Covid-19 cases and deaths in each country colored by GDP and sized by population

Results - variable selection - Mette Chr

Table 1. Correlation between covariants
Estimate Std. Error t value Pr(>|t|)
(Intercept) 200.098826 11.376201 17.589248 0.000000
life_expectancy -0.960407 0.192274 -4.995000 0.000002
population_living_in_urban_areas -0.166332 0.062027 -2.681600 0.008278
respiratory_diseases -156.620453 54.571333 -2.870013 0.004793

Respiratory diseases

- A clear association between COVID-19 case- and mortality kinetics was seen for respiratory diseases

Life expectancy

Population % living in urban areas

PCA analysis by population demographics

  • PCA showed a clear association with COVID-19 kinetics
  • Relative COVID-19 deaths were more informative than absolute deaths
  • PC1 comprises 44.6% of variation

PCA and cluster analysis

  • Cluster analysis (n=3) based on population demographics data (middle) and on PCA (right)
  • Cluster analysis does not capture COVID-19 kinetics accurately

Shiny app - Mette Chr

Sex leader - Mette Christof

Conclusion slide - HJ